TY - JOUR
T1 - Time sequence diffeomorphic metric mapping and parallel transport track time-dependent shape changes.
AU - Qiu, Anqi
AU - Albert, Marilyn
AU - Younes, Laurent
AU - Miller, Michael I.
N1 - Funding Information:
The work reported here was supported by National University of Singapore start-up grant R-397-000-058-133 and A⁎STAR SERC 082-101-0025. The author would like to thank Dr Martin Hadamitzky at Deutsches Herzzentrum, Germany and Dr. Ying Sun at National University of Singapore for providing the cardiac MRI data and the segmented contours of the endocardium and epicardium.
Funding Information:
National University of Singapore start-up grant R-397-000-058-133 and A*STAR SERC 082-101-0025 provided financial support for the conduct of the research.
PY - 2009/3
Y1 - 2009/3
N2 - Serial MRI human brain scans have facilitated the detection of brain development and of the earliest signs of neuropsychiatric and neurodegenerative diseases, monitoring disease progression, and resolving drug effects in clinical trials for preventing or slowing the rate of brain degeneration. To track anatomical shape changes in serial images, we introduce new point-based time sequence large deformation diffeomorphic metric mapping (TS-LDDMM) to infer the time flow of within-subject geometric shape changes that carry known observations through a period. Its Euler-Lagrange equation is generalized for anatomies whose shapes are characterized by point sets, such as landmarks, curves, and surfaces. The time-dependent momentum obtained from the TS-LDDMM encodes within-subject shape changes. For the purpose of across-subject shape comparison, we then propose a diffeomorphic analysis framework to translate within-subject deformation in a global template without incorporating across-subject anatomical variations via parallel transport technique. The analysis involves the retraction of the within-subject time-dependent momentum along the TS-LDDMM trajectory from each time to the baseline, the translation of the momentum in a global template, and the reconstruction of the TS-LDDMM trajectory starting from the global template.
AB - Serial MRI human brain scans have facilitated the detection of brain development and of the earliest signs of neuropsychiatric and neurodegenerative diseases, monitoring disease progression, and resolving drug effects in clinical trials for preventing or slowing the rate of brain degeneration. To track anatomical shape changes in serial images, we introduce new point-based time sequence large deformation diffeomorphic metric mapping (TS-LDDMM) to infer the time flow of within-subject geometric shape changes that carry known observations through a period. Its Euler-Lagrange equation is generalized for anatomies whose shapes are characterized by point sets, such as landmarks, curves, and surfaces. The time-dependent momentum obtained from the TS-LDDMM encodes within-subject shape changes. For the purpose of across-subject shape comparison, we then propose a diffeomorphic analysis framework to translate within-subject deformation in a global template without incorporating across-subject anatomical variations via parallel transport technique. The analysis involves the retraction of the within-subject time-dependent momentum along the TS-LDDMM trajectory from each time to the baseline, the translation of the momentum in a global template, and the reconstruction of the TS-LDDMM trajectory starting from the global template.
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U2 - 10.1016/j.neuroimage.2008.10.039
DO - 10.1016/j.neuroimage.2008.10.039
M3 - Article
C2 - 19041947
AN - SCOPUS:65549104736
SN - 1053-8119
VL - 45
SP - S51-60
JO - NeuroImage
JF - NeuroImage
IS - 1 Suppl
ER -